src/core/errata_logger.py

"""
Errata logging system for tracking data quality issues.

The ErrataLogger captures detailed information about data problems
encountered during processing, enabling post-processing analysis
and data quality reporting.
"""

from pathlib import Path
from typing import Any, Dict, Optional
from datetime import datetime
import json
import logging


class ErrataLogger:
    """
    Logs data quality issues and errors during processing.

    Creates structured log files per dataset with detailed error
    information including file paths, row numbers, error types,
    and the problematic data.
    """

    def __init__(
        self,
        log_dir: str | Path,
        dataset_name: str,
        max_errors: int = 1000
    ):
        """
        Initialize errata logger for a dataset.

        Args:
            log_dir: Directory for errata log files
            dataset_name: Name of the dataset being processed
            max_errors: Maximum errors to log per file (prevents huge logs)
        """
        self.log_dir = Path(log_dir)
        self.log_dir.mkdir(parents=True, exist_ok=True)

        # Create latest directory (for current logs, not gitignored)
        self.latest_dir = self.log_dir.parent / 'latest'
        self.latest_dir.mkdir(parents=True, exist_ok=True)

        self.dataset_name = dataset_name
        self.max_errors = max_errors

        # Create timestamped log file (historical, gitignored)
        timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
        self.log_file = self.log_dir / f"{dataset_name}_{timestamp}_errata.jsonl"

        # Create latest log file (current, not gitignored)
        self.latest_log_file = self.latest_dir / f"{dataset_name}_latest_errata.jsonl"

        # Track error counts
        self.error_counts: Dict[str, int] = {}
        self.total_errors = 0

        # Initialize log files with header
        self._write_header()

    def _write_header(self) -> None:
        """Write log file header with metadata."""
        header = {
            'type': 'header',
            'dataset': self.dataset_name,
            'timestamp': datetime.now().isoformat(),
            'max_errors_per_file': self.max_errors
        }
        self._write_entry(header)

    def _write_entry(self, entry: Dict[str, Any]) -> None:
        """Write a single log entry as JSON line to both timestamped and latest files."""
        # Write to timestamped file (historical)
        with open(self.log_file, 'a') as f:
            f.write(json.dumps(entry) + '\n')

        # Write to latest file (current)
        with open(self.latest_log_file, 'a') as f:
            f.write(json.dumps(entry) + '\n')

    def log_error(
        self,
        error_type: str,
        message: str,
        file_path: Optional[str] = None,
        row_number: Optional[int] = None,
        line_number: Optional[int] = None,
        row_data: Optional[Any] = None,
        context: Optional[Dict[str, Any]] = None,
        scope: str = 'row'
    ) -> None:
        """
        Log a data quality error.

        Args:
            error_type: Type of error (e.g., 'encoding', 'validation', 'schema')
            message: Human-readable error description
            file_path: Path to the file with the error
            row_number: Row number in the DataFrame (0-indexed)
            line_number: Line number in the source file (1-indexed)
            row_data: The problematic data row (if applicable)
            context: Additional context information
            scope: Error scope - 'file' (whole file omitted) or 'row' (single row omitted)
        """
        # Check if we've exceeded max errors for this file
        file_key = file_path or 'unknown'
        if file_key in self.error_counts:
            if self.error_counts[file_key] >= self.max_errors:
                return
        else:
            self.error_counts[file_key] = 0

        # Build log entry
        entry = {
            'type': 'error',
            'error_type': error_type,
            'message': message,
            'scope': scope,  # 'file' or 'row'
            'timestamp': datetime.now().isoformat()
        }

        if file_path:
            entry['file'] = file_path
        if row_number is not None:
            entry['row_number'] = row_number
        if line_number is not None:
            entry['line_number'] = line_number
        if row_data is not None:
            # Convert to string to ensure JSON serializable
            entry['row_data'] = str(row_data)
        if context:
            entry['context'] = context

        self._write_entry(entry)
        self.error_counts[file_key] += 1
        self.total_errors += 1

    def log_file_summary(
        self,
        file_path: str,
        status: str,
        rows_processed: int,
        rows_valid: int,
        rows_invalid: int
    ) -> None:
        """
        Log summary statistics for a processed file.

        Args:
            file_path: Path to the processed file
            status: Processing status ('success', 'partial', 'failed')
            rows_processed: Total rows attempted
            rows_valid: Number of valid rows
            rows_invalid: Number of invalid rows
        """
        entry = {
            'type': 'file_summary',
            'file': file_path,
            'status': status,
            'rows_processed': rows_processed,
            'rows_valid': rows_valid,
            'rows_invalid': rows_invalid,
            'timestamp': datetime.now().isoformat()
        }
        self._write_entry(entry)

    def get_summary(self) -> Dict[str, Any]:
        """
        Get summary of all logged errors.

        Returns:
            Dictionary with error counts and statistics
        """
        error_types = {}
        files_with_errors = len(self.error_counts)

        # Count errors by type by re-reading log file
        with open(self.log_file, 'r') as f:
            for line in f:
                entry = json.loads(line)
                if entry.get('type') == 'error':
                    error_type = entry.get('error_type', 'unknown')
                    error_types[error_type] = error_types.get(error_type, 0) + 1

        return {
            'total_errors': self.total_errors,
            'files_with_errors': files_with_errors,
            'error_types': error_types,
            'log_file': str(self.log_file)
        }

    def close(self) -> None:
        """Close the logger and write final summary."""
        footer = {
            'type': 'footer',
            'summary': self.get_summary(),
            'timestamp': datetime.now().isoformat()
        }
        self._write_entry(footer)